Summary of autonomous systems based on GPT-4: AutoGPT, AgentGPT, BabyAGI, HuggingGPT, CAMEL

The emergence of ChatGPT and LLM technology has made these most advanced language models sweep the world. Not only AI developers, enthusiasts and some organizations are also researching and exploring innovative methods to integrate and build these models. Various platforms have sprung up to integrate and facilitate the development of new applications.

#The popularity of AutoGPT has allowed us to see more and more autonomous tasks and agents taking advantage of the GPT-4 API. These developments not only increase the ability to handle complex tasks of integrating disparate systems, but also push the boundaries of what we can achieve with autonomous artificial intelligence.

Here we will sort out some open source tool systems similar to AutoGPT. These tools and applications can be roughly divided into command line interface (CLI) and browser-based solutions. HuggingGPT can support both solutions. plan.

Command line: AutoGPT, BabyAGI

Browser:AgentGPT, CAMEL, Web LLM

Auto-GPT

Although Auto-GPT is an experimental of open source applications, but its growth is rapid. The program is powered by GPT-4 and can autonomously achieve any goal set.

GitHub: https://github.com/Significant-Gravitas/Auto-GPT

Look at the growth rate of its Github Star. The recent hot

AgentGPT

AgentGPT is a web-based solution. It allows configuring and deploying autonomous AI agents and letting them accomplish any goal. It will try to achieve the goal by thinking about the task to be done, performing the task, and learning from the results.

The platform is currently in beta and the following features are being developed:

• Long-term memory via vector DB
• Through LangChain (LangChain is a platform for building A library for applications of large language models (LLM)) for web browsing
• Interaction with websites and people
• Users and authentication

Git​Hub: https: //github.com/reworkd/AgentGPT

Website: https://agentgpt.reworkd.ai/

BabyAGI

BabyAGI A streamlined version of the task-driven autonomous agent

The main idea is to create tasks based on the results of previous tasks and predefined goals. Then, the script uses OpenAI’s language model function to create new tasks based on goals, and Pinecone to store and retrieve contextual task results. This can be said to be the most streamlined autonomous AI architecture. If you are interested in this direction, you can take a look his code.

GitHub: https://github.com/yoheinakajima/babyagi

Website: http://babyagi.org/

HuggingGPT

Microsoft HuggingGPT, aka JARVIS, consists of an LLM as a controller and a number of expert models as cooperating executors (from HuggingFace Hub). Its workflow consists of four stages:

• Task planning: Use ChatGPT to analyze the request to understand the intent and break it down into possible solvable tasks.
• Model selection: Use ChatGPT to select expert models based on description.
• Task execution: Call and execute each selected model and return the results to ChatGPT.
• Response generation: Finally, use ChatGPT to integrate the predictions of all models and generate a response.

GitHub: https://github.com/microsoft/JARVIS

HF: https://huggingface.co/spaces/ microsoft/HuggingGPT

Web LLM

Web LLM is an LLM-based and LLM-based chatbot that runs within the browser without server support and is accelerated by WebGPU. Technically speaking, Web LLM is not an autonomous solution for artificial intelligence, but a lightweight web chatbot.

GitHub: https://github.com/mlc-ai/web-llm

CAMEL

CAMEL is "Communicative Agents for 'Mind' Exploration of Large Scale Language" Models", it proposes a novel agent framework, role-playing, as an alternative to AutoGPT and AgentGPT.

GitHub: https://github.com/lightaime/camel

Website: http://agents.camel-ai.org/

GPTRPG

This system combines the game with a large language model and mainly consists of 2 parts

A simple rpg-like environment that supports llm's AI agent

Integrate the AI ​​agent into the character of the game environment through the OpenAI API

This is based on a recently published article paper, where multiple agents are deployed to autonomously participate in online games.

​GitHub: https://github.com/dzoba/gptrpg

Arxiv:https://arxiv.org/abs/2304.03442

Summary

Integrating ChatGPT and LLM into a variety of applications is only part of the potential of using language models. These models are designed to handle natural language tasks, including text generation, translation, summarization, question answering, and more. Future language models will be more advanced and intelligent, able to help in a wider range of application areas.

For example, future language models can be used for more accurate machine translation, making cross-cultural communication between humans more convenient. They can also be used for automated summarization and content generation to help authors and media outlets create and publish content faster. In addition, language models can also be used in speech recognition and natural language processing so that people can better interact with computers.

In short, as language model technology continues to advance, we can expect to see more innovation and progress. These models will become the core technology in the field of artificial intelligence, providing us with better solutions and a wider range of application scenarios.

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